Machine Learning-Based Data Analysis / M Deepika, K Kalaiselvi -- Machine Learning for Cyber-Immune IoT Applications / Suchismita Sahoo, Sushree Sangita Sahoo -- Employing Machine Learning Approaches for Predictive Data Analytics in Retail Industry / Rakhi Akhare, Sanjivani Deokar, Monika Mangla, Hardik Deshmukh -- Emerging Cloud Computing Trends for Business Transformation / Prasanta Kumar Mahapatra, Alok Ranjan Tripathy, Alakananda Tripathy -- Security of Sensitive Data in Cloud Computing / Kirti Wanjale, Monika Mangla, Paritosh Marathe -- Cloud Cryptography for Cloud Data Analytics in IoT / N Jayashri, K Kalaiselvi -- Issues and Challenges of Classical Cryptography in Cloud Computing / Amrutanshu Panigrahi, Ajit Kumar Nayak, Rourab Paul -- Cloud-Based Data Analytics for Monitoring Smart Environments / D Karthika -- Performance Metrics for Comparison of Heuristics Task Scheduling Algorithms in Cloud Computing Platform / Nidhi Rajak, Ranjit Rajak -- Smart Environment Monitoring Models Using Cloud-Based Data Analytics: A Comprehensive Study / Pradnya S Borkar, Reena Thakur -- Advancement of Machine Learning and Cloud Computing in the Field of Smart Health Care / Aradhana Behura, Shibani Sahu, Manas Ranjan Kabat -- Study on Green Cloud Computing-A Review / Agrawal Meenal, Jain Ankita -- Intelligent Reclamation of Plantae Affliction Disease / Reshma Banu, GF Ali Ahammed, Ayesha Taranum -- Prediction of the Stock Market Using Machine Learning-Based Data Analytics / P Maheswari, A Jaya -- Pehchaan: Analysis of the 'Aadhar Dataset' to Facilitate a Smooth and Efficient Conduct of the Upcoming NPR / Soumyadev Mukherjee, Harshit Anand, Nishan Acharya, Subham Char, Pritam Ghosh, Minakhi Rout -- Deep Learning Approach for Resource Optimization in Blockchain, Cellular Networks, and IoT: Open Challenges and Current Solutions / Upinder Kaur, Shalu -- Unsupervised Learning in Accordance With New Aspects of Artificial Intelligence / Riya Sharma, Komal Saxena, Ajay Rana -- Predictive Modeling of Anthropomorphic Gamifying Blockchain-Enabled Transitional Healthcare System / Deepa Kumari, BSAS Rajita, Medindrao Raja Sekhar, Ritika Garg, Subhrakanta Panda.

In this era of IoT, edge devices generate gigantic data during every fraction of a second. The main aim of these networks is to infer some meaningful information from the collected data. For the same, the huge data is transmitted to the cloud which is highly expensive and time-consuming. Hence, it needs to devise some efficient mechanism to handle this huge data, thus necessitating efficient data handling techniques. Sustainable computing paradigms like cloud and fog are expedient to capably handle the issues of performance, capabilities allied to storage and processing, maintenance, security, efficiency, integration, cost, energy and latency. However, it requires sophisticated analytics tools so as to address the queries in an optimized time. Hence, rigorous research is taking place in the direction of devising effective and efficient framework to garner utmost advantage. Machine learning has gained unmatched popularity for handling massive amounts of data and has applications in a wide variety of disciplines, including social media. Machine Learning Approach for Cloud Data Analytics in IoT details and integrates all aspects of IoT, cloud computing and data analytics from diversified perspectives. It reports on the state-of-the-art research and advanced topics, thereby bringing readers up to date and giving them a means to understand and explore the spectrum of applications of IoT, cloud computing and data analytics.

Wiley Frontlist Obook All English 2021